Lidar
Showing 36 of 85 projects
An open-source, high-performance platform for developing, testing, and deploying autonomous vehicles.
An open-source project for developing autonomous vehicle software with datasets, models, and ROS components.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A free, open-source WebGL-based point cloud renderer for visualizing massive datasets directly in web browsers.
A curated list of open-source geospatial analysis tools, libraries, and resources across multiple programming languages and domains.
A multi-sensor calibration toolbox for autonomous driving, supporting IMU, LiDAR, camera, and radar calibration.
A Python toolkit for working with the nuScenes and nuImages autonomous driving datasets, providing data loading, visualization, and evaluation utilities.
A lightweight, ground-optimized lidar odometry and mapping system for ROS-compatible unmanned ground vehicles.
A clean, simplified implementation of the LOAM algorithm for real-time LiDAR odometry and mapping using Eigen and Ceres Solver.
A ROS package for real-time 6DOF SLAM using 3D LIDAR, featuring graph-based optimization with multiple sensor constraints.
A modular C++ library implementing the Iterative Closest Point (ICP) algorithm for aligning 2D and 3D point clouds in robotics and computer vision.
A ROS package for extrinsic calibration between LiDAR and camera sensors using 3D-3D point correspondences.
A realtime LiDAR odometry and mapping (LOAM) method for state estimation and mapping using 3D lidar sensors like Velodyne VLP16.
A target-less, automatic toolbox for LiDAR-camera extrinsic calibration that works with various sensor models without requiring calibration targets.
A C++ library for translating and manipulating point cloud data, analogous to GDAL for raster/vector data.
A curated list of awesome LIDAR sensors, datasets, libraries, algorithms, frameworks, and simulators for robotics and autonomous driving.
A curated list of awesome LIDAR sensors, datasets, libraries, algorithms, and simulators for robotics and autonomous driving.
A PyTorch implementation for super fast and accurate 3D object detection using LiDAR point clouds, featuring an anchor-free approach.
A 3D segment-based mapping library for robot localization, environment reconstruction, and semantics extraction using LiDAR data.
A ROS-based method for extrinsic calibration between a 3D LiDAR and a 6-DOF pose sensor using point cloud crispness optimization.
A framework for semantic and instance segmentation of LiDAR point clouds using range images, designed for autonomous driving applications.
An efficient LiDAR-based semantic SLAM system that builds 3D semantic maps from laser scans.
An open-source 3D LIDAR-based mapping framework for semi-automatic, interactive correction of SLAM mapping failures.
A modular C++ and ROS 2 framework for building configurable LiDAR odometry and SLAM pipelines.
A modular ROS package for 3D/6D robot localization and point cloud registration using PCL, with dynamic map updates via OctoMap.
A C++ ROS package for real-time detection, tracking, and classification of static and dynamic objects from LIDAR point clouds.
A ROS voxel layer using OpenVDB for efficient 3D environment representation with temporal decay, replacing voxel_grid for navigation.
ROS 2 LiDAR SLAM for creating non-GPL pointcloud maps compatible with Autoware, featuring loop closure and benchmarking.
Generates an octree LOD structure for streaming and real-time rendering of massive point clouds in web browsers and desktop applications.
A C++ library for fast ground segmentation from LiDAR point clouds using the line-fit algorithm.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
A Siamese neural network for LiDAR-based loop closing and localization by predicting scan overlap and relative yaw angle.
ROS packages for interfacing with Velodyne 3D LIDAR sensors in robotics applications.
A learning-based approach for moving object segmentation in 3D LiDAR data, distinguishing moving vs. static objects in real-time.
A ROS package for calibrating camera and LiDAR sensors using OpenCV's PnP and Levenberg-Marquardt optimization.
A LiDAR-based tool for constructing static maps by removing dynamic points from point cloud sequences.
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